The present invention relates to semantic mapping, and more specifically to semantic mapping of a first topic map meta-model identifying assets to a second topic map meta-model identifying events to form a third topic map meta-model that represents a semantic mapping of assets to events and assigning directionality to the associations between the assets and events in the third topic map meta-model in various scopes identified within another topic map meta-model and storing the directionality in a data structure, the directionality being indicative of a direction of possible impact of an event on one or more assets.
Manufacturing and production based companies have enormous investments in assets and physical infrastructure that are part of the operational processes that drive their business. Optimizing the use of those assets is critical to a company's operational effectiveness and therefore its profitability.
Often times, companies will leverage asset optimization solutions to monitor key performance indicators, leverage analytics to anticipate warning or failure conditions, to schedule maintenance, and optimize resource scheduling against anticipated workload.
One aspect of optimization solutions is the understanding of the relationships between assets and events that could affect them directly or indirectly.
The equipment or assets that run the manufacturing or production processes are generally connected to servers or controllers to generate operational data that can be used to monitor the manufacturing or production process. Typically, companies will collect the operational data and perform operational analysis to provide immediate performance characteristics that can often be represented in dashboards, score sheets, or reports. Information models can be used to represent how assets are deployed and the relationships between assets such as connections, associations or containment. Armed with both the model information and the “real time” operational data, organizations can perform current or future condition analyses on assets and asset groups.
Similarly, organizations may use event models to understand relationships between events within their physical infrastructure. These event models may be explicitly defined, or they could be implicit in the deployment of business operational processes. These processes could be programmatic, rule based, or supplied by a knowledge expert. But independent of how they are manifested, they represent relationships between events that occur within the operational process. For example, the event model would be able to tell a customer what response needs to occur if a critical piece of equipment is operating over a specific threshold, for example running too hot or consuming too much power.